Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis

Abstract

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To Adapt or Not Adapt: Assessing the Adaptive Capacity of Artisanal Fishers in the Trondheimsfjord (Norway) to Jellyfish (Periphylla periphylla) Bloom and Purse Seiners

“…In the workshop setting outlined in this paper, the perceptions of the stakeholders are used to populate these CPTs with probabilities, quantifying their beliefs about the relative importance of different variables within the network. The underlying probabilistic framework (i.e., Bayes theory) provides a mechanism of directly integrating social, economic, and environmental variables within a single model (Kjaerulff and Madsen 2008).…”

A methodology for developing local smart diagnostic models using expert knowledge

“…We apply the model development cycle proposed by [13] illustrated in Figure 2 (taken from [13]) to the development of local smart diagnostic models in the domain of manufacturing. The main steps of this approach are: 1) Begin, 2) Design, 3) Implement, 4) Test, 5) Analyse, and 6) Deploy.…”

“…A Bayesian network (BN) [11], [12], [13] is a probabilistic graphical model that simplify a probabilistic representation by exploiting the marginal and conditional independencies in the domain. Simply speaking, a BN is a pair G, P , where G = (V, E) is an acyclic directed graph (DAG) over a set of random variables V and a set of directed edges E that represent probabilistic relationships between variables V. P is a set of conditional probability distributions (CPDs) that quantify the strength of the relations induced by E. Specifically, P contains for each V ∈ V, the CPDs P (V |pa(V )), where pa(V ) is the set of parent variables of V in G.…”

“…The objective of this step is to identify the variables V and relations E of the DAG G = (V, E). A useful approach to identify the variables of the model is to divide variables into hypothesis, information and mediating variables [13]. In the case of smart diagnostic models, hypothesis variables are the root causes to be considered while information variables are sensor readings, observations from a potential user of the equipment, et cetera.…”

“…This include identifying and correcting undesired behaviours. Possible analysis tools to consider include parameter sensitivity analysis, e.g., [25], [26], [27], but also value of information analysis (VOI), e.g., [37], [38], conflict analysis [39], [40] and evidence sensitivity analysis, e.g., [41], [13].…”